Online social media services, such as social networking sites, news aggregators, blogs, and the like provide a rich environment for users to comment on events of interest and communicate with other users. Messages and other social media content items contributed by users of these social media services often include indirect/colloquial references to events that appear in time-based media (TBM) events such as television shows, news reports, sporting events, concert performances, awards shows, radio programs, festivals, competitions, and the like. Other users who are familiar with the TBM event may recognize these references in messages, but users unfamiliar with the TBM event may not. Consequently, these users may resort to searching through alternative sources of information to understand a reference in a message. Thus, consumers of messages about TBM events would benefit from a more explicit labeling of what TBM event a user is commenting on in a message.
Media recognition technologies provide for identifying unknown snippets of TBMs, but these methods are computationally intensive and typically assume that the unknown snippet is temporally aligned with a matching identifier. If the TBM is concurrently airing, however, then a recorded snippet of the TBM is likely to be temporally misaligned relative to the matching identifier. There are a number of reasons temporal alignment issues can arise. For example, there are often time delays between the recording of the snippet and the broadcasting of the TBM event that generates the matching identifier. There is also usually a time delay in generating the snippet, encoding it if necessary, and communicating it for identification. As a result, current techniques are ill-suited for identifying concurrently broadcasting TBM.